This course will teach a focused managerial strategy of process improvement and variation reduction called Six Sigma, a measure of quality that strives for near perfection.
It is a disciplined, data-driven approach for eliminating defects (driving towards six standard deviations between the mean and the nearest specification limit) in any process-from manufacturing to transactional and from product to service.
A Six Sigma defect is anything outside of customer specifications. To be tagged Six Sigma, a process must not produce more than 3.4 defects per million opportunities.
To this end this course will span established methods of quality assurance and management, and advanced statistical methods including design of experiments.
Positioned at the frontier of modern quality strategies, Six Sigma comprises two frameworks-DMAIC (define, measure, analyze, improve, control) and DMADV (define, measure, analyze, design, verify). This course will cover both.
Basic concepts in Quality Engineering and Management: definitions, approaches and relevance to organizational excellence.
Probability and Statistics-a review.
Total Quality Management perspective, methodologies and procedures; Roadmap to TQM, ISO 9000, KAIZEN, Quality Circles, Quality Models for organizational excellence.
Cost of Quality concepts; finding incentives for improving quality.
Overview of Project Management.
Measurements, Accuracy, precision, Gage R & R.
Product quality control: Acceptance sampling methods-single, multiple and sequential sampling plans; Recent developments in inspection methods.
SPC: Process evaluation and control by control charts: p, c, u, CUSUM and multivariate charts.
Process capability studies: Various indices and approaches; Discussions on capabilities of Process, Machine and Gauge.
Six Sigma Concepts, Steps and Tools.
Quality Function Deployment, QFD example.
Process evaluation and imp-Improvement by Design of Experiments: Various basic designs; Special methods such as EVOP and ROBUST design (Taguchi Methods).
Case Study of Orthogonal Array application.
Robust design by Taguchi Methods.
Case Study of product design by Taguchi Philosophy.
DMAIC-Define, measure, analyze, improve and control-the methodology of Six Sigma implementation.
DMADV-Define, Measure, Analyze, Design and verify-the methodology for creating high performance designs.
Justifying Six Sigma: a Manufacturing Case.
Readiness for Six Sigma-assessing the Organization.
Case Study of initiating Six Sigma DMAIC in Manufacturing.
TQM vs. Six Sigma-The contrast.
Lecture 10: Mod-01 Lec-10 Cost of Quality and TQM Tools